amazon_us_reviews

Riferimenti:

Libri_v1_01

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_01')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 6106719
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Orologi_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Watches_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 960872
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Elettrodomestici per la cura della persona_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Personal_Care_Appliances_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 85981
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Elettronica_mobile_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Electronics_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 104975
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Videogiochi_digitali_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Games_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 145431
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Software_digitale_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Software_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 102084
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Major_elettrodomestici_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Major_Appliances_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 96901
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Gift_Card_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Gift_Card_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 149086
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Video_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 380604
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Bagagli_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Luggage_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 348657
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Software_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Software_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 341931
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_giochi_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Video_Games_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 1785997
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Mobili_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Furniture_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 792113
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Strumenti_musicali_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Musical_Instruments_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 904765
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Acquisto_musica_digitale_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Music_Purchase_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 1688884
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Libri_v1_02

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_02')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 3105520
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Home_Intrattenimento_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Home_Entertainment_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 705889
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Generi alimentari_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Grocery_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 2402458
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

All'aperto_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Outdoors_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 2302401
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Pet_Products_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Pet_Products_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 2643619
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Video_DVD_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Video_DVD_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 5069140
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Abbigliamento_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Apparel_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 5906333
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

PC_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/PC_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 6908554
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Strumenti_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Tools_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 1741100
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Gioielli_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Jewelry_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 1767753
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Bambino_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Baby_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 1752932
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Home_Miglioramento_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Home_Improvement_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 2634781
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Fotocamera_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Camera_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 1801974
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Prato_e_giardino_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Lawn_and_Garden_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 2557288
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Office_Products_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Office_Products_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 2642434
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Elettronica_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Electronics_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 3093869
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Automotive_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Automotive_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 3514942
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Download_video_digitali_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Download_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 4057147
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Mobile_Apps_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Apps_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 5033376
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Scarpe_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Shoes_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 4366916
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Giocattoli_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Toys_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 4864249
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Sport_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Sports_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 4850360
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Cucina_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Kitchen_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 4880466
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Bellezza_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Beauty_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 5115666
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Musica_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Music_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 4751577
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Salute_Cura_personale_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Health_Personal_Care_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 5331449
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Ebook_Purchase_v1_01

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_01')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 5101693
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Casa_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Home_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 6221559
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Wireless_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Wireless_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 9002021
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Libri_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 10319090
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Ebook_Purchase_v1_00

Utilizzare il comando seguente per caricare questo set di dati in TFDS:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_00')
  • Descrizione :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
  • Licenza : nessuna licenza nota
  • Versione : 0.1.0
  • Spaccature :
Diviso Esempi
'train' 12520722
  • Caratteristiche :
{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}